Wolfgang Lechner

𝗖𝗮𝘁𝗰𝗵𝗶𝗻𝗴 𝗮𝗻 𝗶𝗼𝗻 𝘄𝗶𝘁𝗵 𝗮 𝗾𝘂𝗮𝗻𝘁𝘂𝗺 𝗴𝗮𝘀 Hybrid quantum systems involving ultracold atoms and ions are a promising platform for quantum simulation and -computing. In a recently published paper in the journal Physical Review Research, scientists from the Centre for Optical Quantum Technologies at Universität Hamburg report on a robust way to create such a system by capturing an ion in a cloud of ultracold atoms. In recent years, quantum mixtures of ultracold atoms and ions have attracted an increasing interest of researchers in the field of ultracold quantum matter. Processors based on trapped ions are regarded as frontrunners in the field of quantum computing. The new study hints that ultracold atoms may serve as an efficient coolant for these ionic quantum bits. Ludwig Mathey, who also conducts research in the Cluster of Excellence "CUI: Advanced Imaging of Matter" at Universität Hamburg, explains the interplay: "A moving ion can be cooled and stopped completely by a cloud of ultracold atoms. For example, dragging a spoon through a jar filled with honey needs more force than dragging it through air. Similarly, an ion experiences friction by polarizing a Bose-Einstein condensate of ultracold atoms due to its charge." 𝗧𝗵𝗲 𝗽𝗿𝗼𝗰𝗲𝘀𝘀 𝗶𝘀 𝘃𝗲𝗿𝘆 𝗿𝗼𝗯𝘂𝘀𝘁 In a theoretical study, the scientists calculate the time-evolution of the ion, which slows down extremely fast and stops in the quantum gas after traveling a tiny distance of a few hundred nanometers. The higher the initial speed, the more the ion decelerates. “We find that this process is very robust,” says Mathey. In addition, the team related their findings to recent experiments that may catch an ion created by an ultrashort laser pulse in a quantum gas. This would allow quantum simulation of impurity physics, where the bond between atoms and ion alters the ionic movement. Publication in American Physical Society https://lnkd.in/ex-wZzcc Authors Lorenzo Oghittu Juliette Simonet Philipp Wessels-Staarmann Markus Drescher, Klaus Sengstock, Ludwig Mathey and Antonio Negretti

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Today Quantum annealer improves understanding of quantum many-body systems by Forschungszentrum Juelich Artistic rendition of a quantum simulation of 1T-TaS2 being performed on the quantum processing unit of a quantum annealer Physicists have long been pursuing the idea of simulating quantum particles with a computer that is itself made up of quantum particles. This is exactly what scientists at Forschungszentrum Jülich have done together with colleagues from Slovenia. They used a quantum annealer to model a real-life quantum material and showed that the quantum annealer can directly mirror the microscopic interactions of electrons in the material. The result is a significant advancement in the field, showcasing the practical applicability of quantum computing in solving complex material science problems. Furthermore, the researchers discovered factors that can improve the durability and energy efficiency of quantum memory devices. The findings have been published in Nature Communications.

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Heiko Rölke will present our paper on irrational number computations at the International Symposium on Parallel and Distributed Computing (ISPDC)... Abstract Irrational numbers are difficult to compute due to their non-rational nature, i.e. they cannot just be expressed as a ratio consisting of two integer numbers. Various examples of these irrational constants exist, like the circle’s circumference to its diameter π, Euler’s number e, the Golden ratio φ, or the square roots of 2, 3, or 5, and the like. Irrational numbers can be expressed as a sequence of decimal digits just like other real numbers, however, they do not terminate nor do they contain some kind of repeating number pattern. The goal of our work is to efficiently compute and store a very large irrational number by computing as many digits as possible. This test is designed to improve our ability to compute and process extremely large datasets in order to prepare ourselves for future real-world applications based on computational-intensive data analytics concepts, hence high-performance computing is required to solve such data-related problems. To reach these goals we make use of two AMD processors with one terabyte of RAM and 64 cores in total, and an aggregated 510 terabytes of disk space. To run such a computation, we employ 38 hard disk drives running at 7,200 rpm. 34 of these disks are used as swap space and 4 disks will hold the final digits. We illustrate our approach by applying it to the irrational number π and compute 62.8 trillion decimal places of it. Finally, we discuss scalability issues, limitations, challenges, and future directions of our methodology.

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🚀 Chat2Scenario - Scenario Extraction with Large Language Models Yongqi Zhao, Xiao Wenbo, Tomislav Mihalj, Jia Hu, and Arno Eichberger from the Institute of Automotive Engineering at Technische Universität Graz and Tongji University have developed an innovative framework named Chat2Scenario. This novel approach leverages the advanced Natural Language Processing (#NLP) capabilities of Large Language Models (#LLMs) by OpenAI to extract driving scenarios from naturalistic driving datasets. Chat2Scenario efficiently interprets descriptive texts of driving scenarios and utilizes criticality metric thresholds to search for and convert scenarios into ASAM e.V. - Association for Standardization of Automation and Measuring Systems OpenSCENARIO and IPG Automotive CarMaker text files. This methodology not only streamlines the scenario extraction process but also enhances the efficiency of Automated Driving Systems (ADS) validation. By using our #highD dataset, comprising vehicle trajectories on German highways collected via drones, the team demonstrates the potential to simplify complex dataset searches and enhance simulation accuracy. The approach shows how the advances in NLP can help improving ADS testing. Their user-friendly web app provides a practical tool to bridge the gap between naturalistic data and simulation platforms. 📑 Find the link to the paper and the Chat2Scenario tool in the comments below! [1] Yongqi Zhao, Wenbo Xiao, Tomislav Mihalj, Jia Hu, and Arno Eichberger. (2024). Chat2Scenario: Scenario Extraction From Dataset Through Utilization of Large Language Model. Institute of Automotive Engineering, Graz University of Technology, and Tongji University. #Chat2Scenario #NLP #AutomatedDriving #highDdataset #TrafficData #Simulation #VehicleTrajectory #InnovativeResearch #AutonomousVehicles #ScenarioExtraction #FutureOfMobility #EngineeringExcellence #ADSValidation

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Environment modeling for autonomous systems with a usecase in gravel quarries AIT Austrian Institute of Technology scientists Marco Wallner, Matthias Schörghuber and Markus Hofstätter present their paper "A unified Database Schema for geometric and semantic Data: Continuous Volumetric Stocktaking in Gravel Quarries" at the "International Conference on Computer Vision and Applications" in Singapore. The paper focuses primarily on the development of a broadly applicable, generic format for environment modeling. For more click here: https://lnkd.in/dusJ4bxe #computer_vision #automation #environment_modeling

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Congratulations to my student Yunlong Song for successfully defending his Ph.D. in “Learning Robot Control: From #ReinforcementLearning to #DifferentiableSimulation”! Many thanks to the external reviewers Yuke Zhu from the U. of Texas at Austin, Marco Hutter from ETH Zurich, and Martin Riedmiller from Google DeepMind! Yunlong's contributions are: - To show that Reinforcement Learning (RL) outperforms Optimal Control in autonomous racing because it directly optimizes a non-differentiable task-level objective. - To propose a policy-search-for-model-predictive-control (MPC) framework, combining RL's ability to optimize high-level task objectives with MPC's precise actuation and constraint handling. - To introduce a differentiable simulation framework to leverage robot dynamics for more stable and efficient policy training. - To develop a high-performance drone racing system that outperforms optimal control methods and professional pilots. - To develop Flightmare, a flexible modular quadrotor simulator for reinforcement learning and vision-based flight. - Video Recording of the PhD defense: https://lnkd.in/d53QGNck - Yunlong's webpage (publications, source code, slides): https://lnkd.in/dUS68yUH - Google Scholar: https://lnkd.in/d-UMw7bT Congratulations, Yunlong; it has been an honor to work with you! University of Zurich, NCCR Robotics, European Research Council (ERC) UZH Innovation Hub #deeplearning #robotics #machinelearning

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Interesting paper on benchmarking: "Towards Robust Benchmarking of Quantum Optimization Algorithms" by David Bucher, Nico Kraus, Jonas Blenninger, Michael Lachner, Jonas Stein and Claudia Linnhoff-Popien Abstract: Benchmarking the performance of quantum optimization algorithms is crucial for identifying utility for industry-relevant use cases. Benchmarking processes vary between optimization applications and depend on user-specified goals. The heuristic nature of quantum algorithms poses challenges, especially when comparing to classical counterparts. A key problem in existing benchmarking frameworks is the lack of equal effort in optimizing for the best quantum and, respectively, classical approaches. This paper presents a comprehensive set of guidelines comprising universal steps towards fair benchmarks. We discuss (1) application-specific algorithm choice, ensuring every solver is provided with the most fitting mathematical formulation of a problem; (2) the selection of benchmark data, including hard instances and real-world samples; (3) the choice of a suitable holistic figure of merit, like time-to-solution or solution quality within time constraints; and (4) equitable hyperparameter training to eliminate bias towards a particular method. The proposed guidelines are tested across three benchmarking scenarios, utilizing the Max-Cut (MC) and Travelling Salesperson Problem (TSP). The benchmarks employ classical mathematical algorithms, such as Branch-and-Cut (BNC) solvers, classical heuristics, Quantum Annealing (QA), and the Quantum Approximate Optimization Algorithm (QAOA). Link: https://lnkd.in/eh826qZi #quantumcomputing #quantummachinelearning #quantumoptimization #researchpaper #research

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#QuantumComputing | 𝗙𝗶𝗿𝘀𝘁 𝗧𝘄𝗼-𝗾𝘂𝗯𝗶𝘁 𝗚𝗮𝘁𝗲 𝗔𝗰𝗵𝗶𝗲𝘃𝗲𝗱 𝗶𝗻 𝗮 𝗦𝗶𝗹𝗶𝗰𝗼𝗻 𝗧𝗿𝗮𝗻𝘀𝗶𝘀𝘁𝗼𝗿 | Dr. Andreas Kuhlmann and his team at the University of Basel and NCCR SPIN: Spin Qubits in Silicon have achieved the first controllable interaction between two hole spin qubits within the configuration of a conventional silicon transistor. This research remarkably took place within the structure of electronic devices known as "FinFETs," which are at the heart of current smartphone technology and produced in widespread industrial processes. The successful demonstration of controllable qubit interaction opens up vast potential for integrating millions of qubits on a single chip, without the requirement of any extraneous components like micromagnets. The development is instrumental in developing practical, large-scale quantum computers, particularly since reliable, rapid storage, and processing of information are key to the functionality of qubits within these systems. 👉 Learn more >> https://lnkd.in/gYX779e2 👉 Original publication >> https://lnkd.in/gktxd24a 🇨🇭 Follow #ScienceSwitzerland for the latest news and emerging trends on Swiss science, technology, education and innovation >> swissinnovation.org Follow us >> Science-Switzerland #Science | #Education | #Research | #Innovation

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🤩 Ready to have your mind blown by FermiNet's wave function solutions for the Schrödinger equation in our new blog? 🚀 Explore even more enhanced network architectures in quantum chemistry ↓ #MindSpore #casestudy #opensource #AI #DeepMind #Schrodinger

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Check out our latest research on quantum networks from our PhD student Julia Freund together with Alexander Pirker and Wolfgang Dür: In this work "A flexible quantum data bus" we investigate how to route Bell-states on a 2D cluster state between arbitrary sets of pair-wise nodes. The results are very interesting as we manage to show that one can route several Bell-states in parallel running lines without the necessity to sacrifice qubits between the wires. We identify multiple building blocks for routing, including turns, corners and even crossings! This results on a full flexible way how to arrange a quantum data bus from a 2D cluster state. These insights apply to networks of quantum devices of any scale, only pre-requisite is to use a 2D cluster state to connect. Hence, long distance quantum networks benefit from the results but also local area quantum networks using a central hub (that utilizes the cluster state for routing) and even integrated quantum devices similar to small-scale classical networks of integrated circuits (like microcontrollers) connect via busses. Check out all our results here: https://lnkd.in/ejarHgNt

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Key Experiment and Quantum Reasoning | Article by Moritz Waitzmann, Kim-Alessandro Weber, Susanne Wessnigk and Ruediger Scholz https://lnkd.in/eqyaFrGt Leibniz Universität Hannover; MDPI #physics #education #quantum #experiment This article belongs to the Special Issue: Teaching and Learning Quantum Theory and Particle Physics https://lnkd.in/gfrPyezT #Abstract For around five decades, physicists have been experimenting with single quanta such as single photons. Insofar as the practised ensemble reasoning has become obsolete for the interpretation of these experiments, the non-classical intrinsic probabilistic nature of quantum theory has gained increased importance. One of the most important exclusive features of quantum physics is the undeniable existence of the superposition of states, even for single quantum objects. One known example of this effect is entanglement. In this paper, two classically contradictory phenomena are combined to one single experiment. This experiment incontestably shows that a single photon incident on an optical beam splitter can either be reflected or transmitted. The almost complete absence of coincident clicks of two photodetectors demonstrates that these two output states are incompatible. However, when combining these states using two mirrors, we can observe interference patterns in the counting rate of the single photon detector. The only explanation for this is that the two incompatible output states are prepared and kept simultaneously—a typical consequence of a quantum superposition of states. (Semi-)classical physical concepts fail here, and a full quantum concept is predestined to explain the complementary experimental outcomes for the quantum optical “non-waves” called single photons. In this paper, we intend to demonstrate that a true quantum physical key experiment (“true” in the sense that it cannot be explained by any classical physical concept), when combined with full quantum reasoning (probability, superposition and interference), influences students’ readiness to use quantum elements for interpretation.

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A new lecture in the Course: "Introduction to Quantum Computing", has been published: https://lnkd.in/d4AgycWv Lecture 17: The Deutsch-Jozsa Problem In this lecture we generalize the Deutsch's problem. Now the input query function is a function over binary strings of length n, and the goal is to determine again whether the function is constant or balanced, given it is not otherwise as a promise. The quantum solution has an advantage over the classical solution whether deterministic or probabilistic. In addition, the classical probabilistic solution has an advantage over the classical deterministic if we can accept a small possibility of erroneous output. The instruction language is Arabic, however, all material, slides, concepts, definitions, examples, illustrations, etc., are all given in English.

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Turning smallest #sensor nodes into top #AI performers: Rick Pandey, Sebastian Uziel, Tino Hutschenreuther and Silvia Krug will present their new TEEMSC #algorithm that can be fully trained on a #sensor node. It outperforms existing methods for on-device learning. The talk will be at the 2024 IEEE International Workshop on #Metrology for #Industry40 & #IoT in Florence, Italy: https://metroind40iot.org ➡ Why: #predictivemaintenance (PdM) has been a challenge due to insufficient labelled data and dynamic #industrial environments. These problems require a data driven solution for machine degradation analysis which is capable of on-device learning and adapting to the changing industrial environments. Existing data driven unsupervised methods mostly do anomaly detection and the #neuralnetwork-based solutions either rely upon a cumbersome data acquisition and labelling process or suffer from concept drift caused due to changing environmental scenarios. ➡ How: The new TEEMSC algorithm uses singular values and canonical crosscorrelation and enables #energyefficient #machine #diagnosis. TEEMSC can be trained completely on a #sensor node. The learned parameters are adaptive to dynamic industrial scenarios. TEEMSC learns from unlabelled data in mainly unsupervised manner. ➡ #Test: Considering bearing degradation as a PdM scenario the authors have tested the algorithm on PRONOSTIA and XJTU bearing dataset and compared performance of TEEMSC with three existing degradation trend analysis methods namely Principal Component Analysis, Power Spectral Density and Kurtosis on the wavelet decomposition of the original vibration signal. ➡ Performance: Their results can clearly outperform existing unsupervised degradation trend analysis and anomaly detection methods for on-device learning. The algorithm has been developed in the HoLoDEC project. Learn more on the project under www.imms.de/holodec or contact Sebastian Uziel directly. The HoLoDEC project is funded by the German Federal Ministry of Education and Research under the reference 16ME0703.

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[international cooperation] Deutsche Forschungsgemeinschaft (DFG) - German Research Foundation and Japan Science and Technology Agency (JST) have launched a Joint Call for proposals aiming at bilateral projects in Quantum Technologies, an emerging priority area in both Japan and Germany. Proposals submitted to JST and DFG will be evaluated jointly and adopted projects will be respectively supported by both agencies. Japan-based research teams will be supported by JST through the ASPIRE (Adopting Sustainable Partnerships for Innovative Research Ecosystem) programme; Germany-based research teams will be supported by the DFG via a standard research grant (“Sachbeihilfe”). For details please refer to the website of JST: → https://lnkd.in/dAEqWknT DFG Information for Researchers (Call for Proposals, No. 34, 16 April 2024): → https://lnkd.in/dEiybPkH #science #research #Germany #Japan #researchfunding #Quantumtechnology

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Exploring the Future of #DeepTech: GP Lise Rechsteiner, PhD and Maybrit Martschin from Gründerszene talked about key insights into deep tech investing, which companies, who are not in our Portfolio, you should watch, and what an #AIStartup has to possess for her to consider it deep tech. At Vsquared Ventures we examine companies where groundbreaking innovation meets global impact 🚀 But what makes a #deeptech startup truly exceptional? Lise shared her key takeaways and how we analyse and examine the incredible technology companies we get to meet on a daily. Here are some insights: 🔍 𝗙𝗼𝗰𝘂𝘀 𝗼𝗻 𝗗𝗶𝗳𝗳𝗲𝗿𝗲𝗻𝘁𝗶𝗮𝘁𝗶𝗼𝗻: Vsquared Ventures seeks technologies that are not only innovative but also uniquely defensible and scalable. This involves for example new algorithms, hardware, datasets, or a combination of these elements. 💡 𝗚𝗲𝗻𝗲𝗿𝗮𝘁𝗶𝗼𝗻𝗮𝗹 𝗚𝗿𝗼𝘄𝘁𝗵 𝗧𝗵𝗲𝗺𝗲𝘀: We invest in areas that will drive significant change for generations, including #NewSpace, #EnergyTransformation, #AIAndNextGenSoftware, #RoboticsAndManufacturing, #NewComputing, and #TechBio. 🌍 𝗘𝘂𝗿𝗼𝗽𝗲'𝘀 𝗚𝗿𝗼𝘄𝗶𝗻𝗴 𝗗𝗲𝗲𝗽𝘁𝗲𝗰𝗵 𝗟𝗮𝗻𝗱𝘀𝗰𝗮𝗽𝗲: While the US leads in global deeptech investments, Europe is catching up with a surge in growth funds and supportive policies. Notable European startups like Isar Aerospace and IQM Quantum Computers are making significant strides. But there is still room for more: US investors are responsible for 60% of all deep tech investments (Boston Consulting Group (BCG)) and there were roughly 154 IPOs on Wall Street in 2023 compared to 79 in Europe (@Stockanalysis). 📈 𝗜𝗻𝘃𝗲𝘀𝘁𝗺𝗲𝗻𝘁 𝗖𝗿𝗶𝘁𝗲𝗿𝗶𝗮: Vsquared looks for startups with unique, scalable technologies that solve real problems, have a potential for global growth, and possess a well-rounded, ambitious team. Here are five promising deeptech startups from the DACH region that we recommend watching: 🔋 Dunia: Transforming energy by AI-driven materials discovery ⚡ Lightium: Building "All-optic" chips for faster data processing. 💡 Akhetonics: Creating ultra-fast, energy-efficient computer chips. 🤖 Flink Robotics: Enhancing industrial robots with advanced AI. ✈️ Metafuels: Producing sustainable aviation fuel from renewable electricity. The future of deeptech is bright, and Europe's role is becoming increasingly pivotal. It is our mission at Vsquared Ventures to continue to empower founders building companies based on groundbreaking technologies, creating new markets and becoming global leaders out of Europe to make the region future-proof. Read the full article here: https://lnkd.in/eNbjxhEy And reach out if you are a founder who is building a company in this space! #Deeptech #Innovation #Startups #VsquaredVentures #Technology #Investment #Europe

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Fancy Labs, Big Dreams: Building the Future of Quantum Networks Ever dreamt of shaping the future of technology? Tobias Heindel from Technische Universität Berlin has a vision for a groundbreaking institute dedicated to solid-state quantum networking. This institute would be a collaborative hub, housing three distinct research groups. By bringing together diverse expertise, we can tackle the key challenges in this emerging field and accelerate progress. Are you too a passionate researcher? Let us know your biggest wish in the comments below. Podcast Host: Dr. Pranoti Kshirsagar #quantumcomputing #quantumnetwork #solidstate #research #underthemicroscope #thesciencetalk

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In a study produced as part of my postdoctoral research at Politecnico di Milano, funded by FAPESP, we report a new study published in *Nature Quantum Information* (2024), showing the high-fidelity generation of 4-photon Greenberg-Horne-Zeilinger (GHZ) states on a chip, a significant breakthrough for all-optical quantum technologies. This work highlights the integration of a bright quantum-dot based single-photon source with a low-loss reconfigurable glass photonic circuit, achieving unprecedented results in on-chip entanglement generation. The paper, titled "High-fidelity four-photon GHZ states on chip", https://lnkd.in/dQfE4ybc, with Fabio Sciarrino, Marco Liscidini, Nadia Belabas, and Roberto Osellame as key contributors. Our research focused on the generation of 4-photon GHZ states using a quantum-dot based single-photon source and a glass photonic circuit. We achieved an experimental fidelity to the target state of 86% and a purity of 76% through full quantum-state tomography. The entanglement was certified using a semi device-independent approach, violating a Bell-like inequality by more than 39 standard deviations. Additionally, we demonstrated a four-partite quantum secret sharing protocol on-chip, achieving a qubit-error rate of 10.87% with a sifted key of up to 1978 bits. These results underscore the potential of quantum-dot technology combined with glass photonic circuitry for scalable and high-rate entanglement generation. The systematic analysis and numerical modeling identified photon indistinguishability as the main factor limiting fidelity. Improvements in voltage source stability, temporal overlap, and polarization control are expected to enhance performance further. Reducing insertion losses and increasing operation rates to at least 500 MHz will also improve fidelity and purity, enabling higher bitrates and lower error rates in quantum protocols. Overall, our findings mark a significant milestone in the integration of quantum-dot based single-photon sources with photonic chips, demonstrating that this platform is mature enough for practical quantum devices. The long-term stability and potential for integrability of our quantum-dot source, combined with the reconfigurable optical elements in our photonic chip, position this technology at the forefront of developing practical photon-based quantum devices.

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